Removing Characters: Method 2
As mentioned, there are two ways to remove a character from all column values. The second method uses a lambda
function. How does it work? You define a lambda
function that removes a certain character/characters from a function variable, and apply it to the selected column. Then you convert obtained values to the necessary type and save them.
Swipe to start coding
- Define a lambda function with a single argument
x
that will look for and delete any of the characters'$°C%'
from both the left and right sides (using the.strip()
method). Assign the function to therm
variable. - Apply the
rm
function to the'Fuel_Price'
column and then convert it to numerical type (float
) using the.astype()
method. Assign the obtained result to the same column. - Perform the same actions described in the step 2 for the
'Unemployment'
column. - Perform the same actions described in the step 2 for the
'Temperature'
column. - Display the first row of the
df
dataframe and data types of thedf
dataframe.
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Removing Characters: Method 2
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As mentioned, there are two ways to remove a character from all column values. The second method uses a lambda
function. How does it work? You define a lambda
function that removes a certain character/characters from a function variable, and apply it to the selected column. Then you convert obtained values to the necessary type and save them.
Swipe to start coding
- Define a lambda function with a single argument
x
that will look for and delete any of the characters'$°C%'
from both the left and right sides (using the.strip()
method). Assign the function to therm
variable. - Apply the
rm
function to the'Fuel_Price'
column and then convert it to numerical type (float
) using the.astype()
method. Assign the obtained result to the same column. - Perform the same actions described in the step 2 for the
'Unemployment'
column. - Perform the same actions described in the step 2 for the
'Temperature'
column. - Display the first row of the
df
dataframe and data types of thedf
dataframe.
Рішення
Дякуємо за ваш відгук!
Awesome!
Completion rate improved to 3.45single